基于分布式状态转移算法的有色冶金过程系统辨识方法研究

项目名称： 基于分布式状态转移算法的有色冶金过程系统辨识方法研究

项目编号： No.61503416

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 周晓君

作者单位： 中南大学

项目金额： 22万元

中文摘要： 有色冶金过程的优化控制需要建立在系统模型的基础上，而模型的确定需要通过系统辨识的方法实现。实际有色冶金过程机理复杂、工艺流程长等特点，导致其系统辨识难以选择模型结构、优化模型参数。为此，本项目在研究机理建模和数据建模内在联系的基础上，提出机理分析和函数逼近相集成的有色冶金过程系统模型结构选择方法，同时考虑模型结构和辨识准则共同影响优化问题目标函数性态，研究与优化算法相融合的辨识准则设计方法， 实现目标函数性态的改造，便于优化算法求解；并进一步研究目标函数的可分性，提出基于分布式状态转移算法的模型参数优化方法，提高辨识过程的快速性；结合仿真研究和湿法炼锌净化除钴过程工程应用研究，验证所提方法的可行性和有效性；形成较为系统的面向有色冶金过程的系统辨识理论和方法，并为其它非线性工业过程系统辨识提供借鉴。

中文关键词： 分布式优化；状态转移算法；非线性系统辨识；有色冶金过程；过程建模

英文摘要： To realize the optimal control of nonferrous metallurgy processes, it is necessary to establish system models with structures and parameters, while the system models are achieved by system identification approaches. It is very difficult to select model structures and optimize model parameters for system identification in practical nonferrous metallurgy processes due to their complex mechanisms and long technological flow. In this project, we will start with the model structure selection problem. We aim to propose an integrated model structure selection approach composed of mechanism analysis and function approximation by cooperating with identification criterion design methods and optimization techniques, in order to improve the properties of the objective functions in optimization problems. Then, by analyzing the separability of the objective functions, we will propose a model parameter estimation approach based on distributed state transition algorithm to accelerate the nonlinear system identification process. Finally, the proposed approaches will be applied to the cobalt removal process in zinc hydrometallurgy to testify their feasibility and effectiveness. A systematic system identification theory is expected to be formed for nonferrous metallurgy processes, which will provide references for other nonlinear industrial processes.

英文关键词： distributed optimization;state transition algorithm;nonlinear system identification;nonferrous metallurgy process ;process modeling